制冷技术2025，Vol.45Issue(2)：71-76,6.DOI:10.3969/j.issn.2095-4468.2025.02.203
基于反向传播神经网络和遗传算法的地源热泵运行策略优化
Optimization of Ground Source Heat Pump Operation Strategy Based on Back Propagation Neural Network and Genetic Algorithm
王海波 1田彦法 2王涛 3周世玉 1刘吉营1
作者信息
- 1. 山东建筑大学热能工程学院,山东 济南 250101
- 2. 山东华科规划建筑设计有限公司,山东 聊城 252000
- 3. 山东省地质矿产勘查开发局八〇一水文地质工程大队,山东 济南 250014
- 折叠
摘要
Abstract
To address the issue of non-energy-efficient behavior resulting from human operations during system runtime,this study utilizes cumulative operational data from the 2022 cooling season to establish a back propagation neural network energy consumption prediction model.The model is subsequently validated,with the average error meeting precision requirements.Leveraging the energy consumption prediction model,a genetic algorithm is employed for optimization,and the results are compared with those obtained through manual experiential adjustments.The findings indicate that,energy savings are achieved through parameter adjustments using the genetic algorithm outperform those based on human experience.Notably,within the load interval accounting for the longest operational duration(from 30%to 50%),energy savings reach 7.84%.关键词
地源热泵/反向传播神经网络/遗传算法/能耗Key words
Ground source heat pump/Back propagation neural network/Genetic algorithm/Energy consumption分类
通用工业技术引用本文复制引用
王海波,田彦法,王涛,周世玉,刘吉营..基于反向传播神经网络和遗传算法的地源热泵运行策略优化[J].制冷技术,2025,45(2):71-76,6.
